Aether AI-Sec Platform

Aether is an AI orchestration platform that routes requests across multiple LLM providers (OpenAI, Anthropic, Google) based on cost, latency, and capability requirements. It was built to solve a real problem: enterprise teams need to use different models for different tasks, and managing multiple API integrations is painful.

The architecture is a Python FastAPI backend with a Next.js frontend. The routing engine evaluates each request against provider capabilities, current latency percentiles, and cost constraints to pick the optimal model. Results stream back to the client via Server-Sent Events.

Key engineering challenges included building a streaming proxy that handles backpressure correctly, implementing token-level cost tracking across providers with different pricing models, and designing a prompt template system that adapts to each model's format requirements.

The platform handles 10K+ concurrent WebSocket connections using Redis pub/sub for horizontal scaling. Each API gateway instance is stateless — session state lives in Redis, and the routing decisions are made by a shared scoring service.

Security was critical since enterprise customers send sensitive data through the platform. We implemented end-to-end encryption, SOC 2-compliant audit logging, and a zero-retention mode where prompts and responses are never stored.